Other

This included data from the NLTS2 Waves 1 to Wave 4 parent/youth phone interview and/or mail survey data (Wave 1 was collected in the 2000–2001; Wave 2 was collected in the 2002–2003; Wave 3 was collected in the 2004–2005; and Wave 4 was collected in the 2006–2007 school years) and Wave 1 to Wave 2 school program survey data (Wave 1 was collected in the 2001–2002 and Wave 2 was collected in the 2003–2004 school years). The information was gathered for the first time in the 2000–2001 school year and last time in the 2006–2007 school year. SAS 9.2 was used for statistical analyses. All the data used had no missing values. The cases containing missing values were removed. Variables were described using descriptive statistics. Continuous variables, values were reported as means ± standard deviations (SDs). Categorical variables, values were reported as percents. A three-step process was used to determine the factors significantly associated with participation in employment for students with autism.

Researchers performed descriptive univariate analyses for all variables. Researchers were concerned that depression knowledge and attitudes might vary among the work sites, especially among the healthcare industries compared with the non-health care industries. Therefore, researchers examined response differences among company sites. Nevertheless, companies generally were similar in structure, urban location, employee socio-demographics (per general employer-published reports), health care availability, and health care insurance programs. Additionally, most companies were lacking in prior depression awareness-raising programs.

Researchers were also concerned that respondents with a history of depression might have different knowledge, attitudes, and help-seeking behavior than those without a history of depression. Therefore, we examined response differences between those with and without a self-reported depression history.

Field observations revealed none of the participants got lost. A number of scenarios were set up to test the advance functions of the system. An evaluation also took place. The information gained was used to convince job coaches to participate in upcoming trials and give feedback about how to improve the design.

Participants were asked to complete a shipping task that involved an average of 73 steps. The percentage of task steps completed correctly was calculated by dividing the number of relevant completed steps by the sum of relevant completed and relevant not completed steps and multiplying by 100.

Pre-test, post-test, and improvement scores were collected.

One and half hour semi structured telephone interviews were conducted with program managers using the Quality of Supported Employment Implementation Scale. The subscales were: vocational staffing, organization and services, from the Individual Placement and Support Fidelity Scale. After the interview, procedures were explained about collecting employment outcome data. Program directors were paid $100 for completing this activity. The data related to employment status of current consumers.

Employment data was collected on participants, including wages and job tenure was collected.

This article reviews the emerging literature examining the psychometric adequacy and practical utility of the IPS Fidelity Scale, addressing the following questions: (1) Does the IPS Fidelity Scale display appropriate psychometric properties (adequate reliability, content and discriminative validity, and sensitivity to change)? (2) Do programs that score higher in IPS fidelity have better employment outcomes? (3) Is the IPS Fidelity Scale a useful tool for guiding implementation in multisite projects? (4) Is the IPS Fidelity Scale useful for accrediting programs for funding decisions? (5) Is the IPS Fidelity Scale useful for monitoring purposes in formal research studies? For the first two questions, we provide quantitative evidence from published and unpublished studies. Our evidence for the remaining three questions is primarily descriptive and anecdotal.

The study compared Individual Placement and Support and treatment as usual with treatment as usual alone. A series of logistic regression analyses were conducted to assess the predictive power of demographic and clinical factors on vocational recovery.

Data was collected by telephone within two weeks of the last meeting with the counselor and again at 6 months.